code: def login(
      backend: str = "databricks", interactive: bool = True
  ) -> None:
      """Configure MLflow server authentication and connect MLflow to tracking server.
  
      This method provides a simple way to connect MLflow to its tracking server. Currently only
      Databricks tracking server is supported. Users will be prompted to enter the credentials if no
      existing Databricks profile is found, and the credentials will be saved to `~/.databrickscfg`.
  
      Args:
          backend: string, the backend of the tracking server. Currently only "databricks" is
              supported.
  
          interacive: bool, controls request for user input on missing credentials. If true, user
              input will be requested if no credentials are found, otherwise an exception will be
              raised if no credentials are found.
  
      .. code-block:: python
          :caption: Example
  
          import mlflow
  
          mlflow.login()
          with mlflow.start_run():
              mlflow.log_param("p", 0)
      """
      from mlflow.tracking import set_tracking_uri
  
      if backend == "databricks":
          _databricks_login(interactive)
          set_tracking_uri("databricks")
      else:
          raise MlflowException(
              f"Currently only 'databricks' backend is supported, received `backend={backend}`."
          )
  
file_path: mlflow/mlflow/utils/credentials.py
imports: import configparser
  import getpass
  import logging
  import os
  import subprocess
  from typing import NamedTuple, Optional, Tuple
  from mlflow.environment_variables import MLFLOW_TRACKING_PASSWORD, MLFLOW_TRACKING_USERNAME
  from mlflow.exceptions import MlflowException
label_desc: Use image node_id 5 for calling a global function with example usage: login(backend, interactive) without return types